2 citations · 5 across the 8 of their papers we have counts for
9 papers
Document-Level Language Models for Machine Translation
Frithjof Petrick, Christian Herold, Pavel Petrushkov +2
Despite the known limitations, most machine translation systems today still operate on the sentence-level. One reason for this is, that most parallel training data is only sentence…
Improving Long Context Document-Level Machine Translation
Christian Herold, Hermann Ney
Document-level context for neural machine translation (NMT) is crucial to improve the translation consistency and cohesion, the translation of ambiguous inputs, as well as several…
On Search Strategies for Document-Level Neural Machine Translation
Christian Herold, Hermann Ney
Compared to sentence-level systems, document-level neural machine translation (NMT) models produce a more consistent output across a document and are able to better resolve ambigui…
Improving Language Model Integration for Neural Machine Translation
Christian Herold, Yingbo Gao, Mohammad Zeineldeen +1
The integration of language models for neural machine translation has been extensively studied in the past. It has been shown that an external language model, trained on additional…
Does Joint Training Really Help Cascaded Speech Translation?
Viet Anh Khoa Tran, David Thulke, Yingbo Gao +2
Currently, in speech translation, the straightforward approach - cascading a recognition system with a translation system - delivers state-of-the-art results. However, fundamental…
Is Encoder-Decoder Redundant for Neural Machine Translation?
Yingbo Gao, Christian Herold, Zijian Yang +1
Encoder-decoder architecture is widely adopted for sequence-to-sequence modeling tasks. For machine translation, despite the evolution from long short-term memory networks to Trans…
Revisiting Checkpoint Averaging for Neural Machine Translation
Yingbo Gao, Christian Herold, Zijian Yang +1
Checkpoint averaging is a simple and effective method to boost the performance of converged neural machine translation models. The calculation is cheap to perform and the fact that…
Diving Deep into Context-Aware Neural Machine Translation
Jingjing Huo, Christian Herold, Yingbo Gao +3
Context-aware neural machine translation (NMT) is a promising direction to improve the translation quality by making use of the additional context, e.g., document-level translation…
Exploring Kernel Functions in the Softmax Layer for Contextual Word Classification
Yingbo Gao, Christian Herold, Weiyue Wang +1
Prominently used in support vector machines and logistic regressions, kernel functions (kernels) can implicitly map data points into high dimensional spaces and make it easier to l…